• Leverage data expertise to analyze a wide spectrum of data to provide insights and solutions to the business. • Identify and improve inefficiencies or issues in current data processes and reports with a “there’s always room for improvement” mindset. • Conceive, design & develop purpose focused reports and dashboards that drive value and meets business needs. • Manipulate large data sets from multiple sources to provide business metric reporting. • Communicate concise and actionable business strategies from vast amounts of data to senior management. • Continuously broaden knowledge of different business verticals and their functions and how they utilize data. • Lead the regular touchpoint with business stakeholders to provide insights beyond what is requested and/or provide data solutions to improve their workflow. • Conduct advanced statistical and financial analysis to uncover trends, patterns, and business opportunities. • Leverage statistical modeling, predictive analytics, and machine learning techniques to provide deeper insights into business operations and market conditions. • Produce high-quality, visually compelling reports and dashboards using tools such as Tableau, Power BI, or Excel for stakeholders at all levels. • Support the Sr. Manager of Analytics in defining key metrics, performance targets, and project priorities for the department.

• Use data to understand our users -- what they need, what they do, how to retain them, and ultimately how to help them find the best dates. • Partner with cross-functional teams to provide long-term strategic insights for our products. • Support business trends/forecasting and model the financial impact of new product ideas. • A strong knowledge querying massive and complex datasets, analyzing, and driving key and actionable insights. • Working with other cross-functional teams like Finance, CRM, Engineering and Business Intelligence; proactively engage other teams to identify and drive better user experience. • Providing internal consulting to product management, marketing, finance, and CRM teams on A/B tests as they move initiatives from concept to market. • Presenting technical content across business stakeholders. • Working as the product owner of revenue and retention strategies for the product. • Serving as the subject matter expert on applying various statistical methodologies towards distilling actionable insights. • Researching issues about customer behavior/changes by analyzing relevant metrics, trends and supporting enterprise level initiatives.

• Define and maintain key product indicators and a structured metrics tree to ensure consistent measurement across exchange and trading operations. • Prepare, visualize, and clearly present data needed for informed and timely decision-making. • Build informative dashboards and reports in Tableau for product, operational, and leadership teams. • Monitor product and trading performance by analyzing core metrics, feature output, execution quality, and market behavior. • Identify inefficiencies, anomalies, or risks — including suboptimal liquidity providers, algorithm behavior issues, or operational bottlenecks. • Evaluate the performance of trading algorithms and extract actionable insights to improve execution quality and profitability. • Conduct statistical and quantitative analyses, including back-tests, regressions, and time-series evaluations to validate hypotheses and support product improvements. • Perform ad-hoc deep-dive analyses based on business and operational requests. • Prepare new analytical reports and implement alerting mechanisms for key metrics and deviations. • Work closely with product and engineering teams to define analytical requirements and support a data-driven approach across the organization.

• Partner closely with two core product squads and their product managers to understand goals, define success metrics, and translate product ideas into concrete analytical plans. • Design and execute experiments on new and existing features, including scoping test populations, determining rollout strategies, and monitoring “do no harm” tests where sample sizes are smaller. • Write high-quality, efficient SQL (primarily in Snowflake via Hex) to investigate product questions, build custom analyses, and create clear, reusable queries that power reporting and decision-making. • Define tracking requirements for new features and collaborate with engineers and designers to ensure the right data is captured from day one, enabling robust analysis over the lifecycle of a feature. • Analyze experiment and feature performance data, synthesize findings into clear narratives, and make concrete, data-backed recommendations to product managers and business stakeholders (including when to roll back changes). • Collaborate closely with the analytics team (including your manager and peer analysts) for code reviews, feedback, and shared best practices, while independently driving your own roadmap and owning outcomes in your domain.